Average Error: 6.2 → 2.6
Time: 3.4s
Precision: 64
\[x - \frac{y \cdot \left(z - t\right)}{a}\]
\[x + \left(-\frac{y}{a}\right) \cdot \left(z - t\right)\]
x - \frac{y \cdot \left(z - t\right)}{a}
x + \left(-\frac{y}{a}\right) \cdot \left(z - t\right)
double code(double x, double y, double z, double t, double a) {
	return (x - ((y * (z - t)) / a));
}
double code(double x, double y, double z, double t, double a) {
	return (x + (-(y / a) * (z - t)));
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Bits error versus a

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original6.2
Target0.7
Herbie2.6
\[\begin{array}{l} \mathbf{if}\;y \lt -1.07612662163899753 \cdot 10^{-10}:\\ \;\;\;\;x - \frac{1}{\frac{\frac{a}{z - t}}{y}}\\ \mathbf{elif}\;y \lt 2.8944268627920891 \cdot 10^{-49}:\\ \;\;\;\;x - \frac{y \cdot \left(z - t\right)}{a}\\ \mathbf{else}:\\ \;\;\;\;x - \frac{y}{\frac{a}{z - t}}\\ \end{array}\]

Derivation

  1. Initial program 6.2

    \[x - \frac{y \cdot \left(z - t\right)}{a}\]
  2. Using strategy rm
  3. Applied clear-num6.2

    \[\leadsto x - \color{blue}{\frac{1}{\frac{a}{y \cdot \left(z - t\right)}}}\]
  4. Using strategy rm
  5. Applied sub-neg6.2

    \[\leadsto \color{blue}{x + \left(-\frac{1}{\frac{a}{y \cdot \left(z - t\right)}}\right)}\]
  6. Simplified2.6

    \[\leadsto x + \color{blue}{\left(-\frac{y}{a}\right) \cdot \left(z - t\right)}\]
  7. Final simplification2.6

    \[\leadsto x + \left(-\frac{y}{a}\right) \cdot \left(z - t\right)\]

Reproduce

herbie shell --seed 2020058 
(FPCore (x y z t a)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, F"
  :precision binary64

  :herbie-target
  (if (< y -1.0761266216389975e-10) (- x (/ 1 (/ (/ a (- z t)) y))) (if (< y 2.894426862792089e-49) (- x (/ (* y (- z t)) a)) (- x (/ y (/ a (- z t))))))

  (- x (/ (* y (- z t)) a)))